SimRisk: An Integrated Open-Source Tool for Agent-Based ...
SimRisk: An Integrated Open-Source Tool for Agent-Based ...
SimRisk: An Integrated Open-Source Tool for Agent-Based ...
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Q1/2010 Q2/2010 Q3/2010 Q4/2010 Q1/2011 Q2/2011 Q3/2011 Q4/2011 Q1/2012 Q2/2012 Q3/2012 Q4/2012<br />
<strong>Agent</strong>-based Stochastic Modeling<br />
Extension of Markov Decision Processes<br />
Component-based design<br />
Model reusability<br />
Support <strong>for</strong> decision optimization<br />
Re-targetable generative simulation engine<br />
Load balance based on structure<br />
in<strong>for</strong>mation<br />
Thread-scheduling optimization<br />
Formal stochastic analysis<br />
Pattern-based problem <strong>for</strong>mulation<br />
Proof extract and game-based<br />
interpretation<br />
<strong>Open</strong> source tools development<br />
Table 1: The project timeline.<br />
5.5 Project timeline<br />
Table 1 gives the project timeline. The project will be carried out in a three-year period with ef<strong>for</strong>ts<br />
of two faculty members, one Ph.D. student, and one Masters student. Table 1 lists durations and<br />
finish time of activities defined <strong>for</strong> each specific aim.<br />
5.6 Project management<br />
In this project Li Tan will lead ef<strong>for</strong>ts on developing high-per<strong>for</strong>mance reconfigurable simulation<br />
technology, automated <strong>for</strong>mal stochastic analysis technique, and the open-source tool Simrisk.<br />
Shenghan Xu will lead ef<strong>for</strong>ts on agent-based stochastic modeling and the empirical study of new<br />
technologies developed in this project. The University of Idaho and Washington State University<br />
Pullman campus are connected by a 7-mile highway. During the course of this project we will hold<br />
weekly research meeting between two groups.<br />
6 Broader impact<br />
Stochastic analysis of supply chains is important <strong>for</strong> a wide range of applications, including risk<br />
supply-chain risk analysis[Chen and Zhang, 2008], contracting [van Delft and Vial, 2004], and<br />
per<strong>for</strong>mance evaluation [Wei et al., 2007]. We expect that the success of this project will advance<br />
research on these application. Because of the practical significance of stochastic analysis<br />
in supply-chain management, the project is also expected to assist companies who are interested<br />
in streamlining their supply chains. In addition, we plan to promote knowledge dissemination<br />
and technology transfer by publications, the distribution of an open-source tool, and educational<br />
programs. Theories and methods developed in this project will be shared in research community<br />
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